DuckDB’s json_type() function is a useful utility for inspecting JSON data structures. It helps us determine what type of data we’re working with at any level within a JSON document. This function can be handy when we need to validate data types or handle different JSON structures programmatically.
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JSON_EXTRACT() vs JSON_EXTRACT_STRING() in DuckDB: What’s the Difference?
DuckDB has a json_extract() function that extracts JSON from a JSON document. DuckDB also has a function called json_extract_string() that does a similar thing, but extracts its value as a string.
This article takes a look at these two functions side by side.
Get the Number of Elements in a JSON Array with JSON_ARRAY_LENGTH() in DuckDB
In DuckDB, the json_array_length() function is used to determine the number of elements in a JSON array. This function can return the count of items in the top-level array or in a nested array within it. It’s especially useful when working with complex JSON structures where arrays are embedded inside objects or other arrays. By combining it with JSON path expressions, you can target specific portions of the data for more precise analysis.
Understanding the JSON_GROUP_STRUCTURE() Function in DuckDB
The json_group_structure() function in DuckDB is an aggregate function that inspects all JSON values within a group and returns a JSON representation of their structure. It essentially infers a “schema” for the JSON objects in that group. This can be useful for understanding the shape and consistency of your JSON data.
A Quick Look at DuckDB’s JSON_STRUCTURE() Function
In DuckDB, the json_structure() is used to parse and introspect JSON data, returning the structure of a JSON document. This is especially useful when you’re working with semi-structured JSON data and you want to understand its schema — including nested keys, arrays, and types — without manually inspecting the raw JSON.
Understanding DuckDB’s JSON_VALID() Function
Most of the major RDBMSs that support JSON also include a json_valid() function for checking the validity of a JSON document, and DuckDB’s no exception. Like the other RDBMSs, DuckDB’s implementation of json_valid() checks its argument and returns a boolean value to indicate whether or not it’s valid JSON.
A Quick Look at DuckDB’s JSON_VALUE() Function
DuckDB provides a handful of functions for getting data from JSON documents. We can use them as long as the JSON extension is installed and loaded (which it is in most distributions). One such function for getting data from a JSON document is json_value(). This function extracts scalar data from the specified path in the JSON document. If the value isn’t scalar, then a NULL value is returned.
Understanding JSON_EXTRACT_STRING() in DuckDB
DuckDB has a json_extract_string() function that works similar to json_extract(), except that it returns its result as a string (varchar). The json_extract() function, on the other hand, returns its result as JSON.
The purpose of these two functions is to extract data from a JSON document. We’ll focus on the json_extract_string() function in this article.
Using JSON_EXTRACT() in DuckDB
DuckDB has a json_extract() function that extracts JSON data from a JSON document. It enables us to get JSON values from within the JSON document, rather than returning the whole document itself. This article takes a quick look at the function along with some examples of usage.
DuckDB JSON_EXISTS(): Check if a Path Exists in a JSON Document
Most DuckDB distributions are shipped with the json extension, which enables us to work with JSON documents. DuckDB provides a bunch of JSON functions, including JSON_EXISTS(). The JSON_EXISTS() function allows us to check whether a specific path exists within a JSON document.
This article explores how this function works, along with examples.